The inaugural title in the new, Open Access series BSPS Open, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. The fundamental burden of a theory of inductive inference is to determine which are the good inductive inferences or relations of inductive support and why it is that they are so. The traditional approach is modeled on that taken in accounts of deductive inference. It seeks universally applicable schemas or rules or a (...) single formal device, such as the probability calculus. After millennia of halting efforts, none of these approaches has been unequivocally successful and debates between approaches persist. The Material Theory of Induction identifies the source of these enduring problems in the assumption taken at the outset: that inductive inference can be accommodated by a single formal account with universal applicability. Instead, it argues that that there is no single, universally applicable formal account. Rather, each domain has an inductive logic native to it. Which that is, and its extent, is determined by the facts prevailing in that domain. Paying close attention to how inductive inference is conducted in science and copiously illustrated with real-world examples, The Material Theory of Induction will initiate a new tradition in the analysis of inductive inference. (shrink)

Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the "external" parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered (...) in the internal stages of science: choice of methodology, characterization of data, and interpretation of results. (shrink)

Inductive methods can be used to estimate the accuracies of inductive methods. Call a method immodest if it estimates that it is at least as accurate as any of its rivals. It would be unreasonable to adopt any but an immodest method. Under certain assumptions, exactly one of Carnap's lambda-methods is immodest. This may seem to solve the problem of choosing among the lambda-methods; but sometimes the immodest lambda-method is λ =0, which it would not be reasonable to adopt. We (...) should therefore reconsider the assumptions that led to this conclusion: for instance, the measure of accuracy. (shrink)

In the mid-eighteenth century David Hume argued that successful prediction tells us nothing about the truth of the predicting theory. But physical theory routinely predicts the values of observable magnitudes within very small ranges of error. The chance of this sort of predictive success without a true theory suggests that Hume's argument is flawed. However, Colin Howson argues that there is no flaw and examines the implications of this disturbing conclusion; he also offers a solution to one of the central (...) problems of Western philosophy, the problem of induction. (shrink)

Contrary to formal theories of induction, I argue that there are no universal inductive inference schemas. The inductive inferences of science are grounded in matters of fact that hold only in particular domains, so that all inductive inference is local. Some are so localized as to defy familiar characterization. Since inductive inference schemas are underwritten by facts, we can assess and control the inductive risk taken in an induction by investigating the warrant for its underwriting facts. In learning (...) more facts, we extend our inductive reach by supplying more localized inductive inference schemes. Since a material theory no longer separates the factual and schematic parts of an induction, it proves not to be vulnerable to Hume's problem of the justification of induction. (shrink)

The pessimistic induction plays an important role in the contemporary realism/anti-realism debate in philosophy of science. But there is some disagreement about the structure and aim of the argument. And a number of scholars have noted that there is more than one type of PI in the philosophical literature. I review four different versions of the PI. I aim to show that PIs have been appealed to by philosophers of science for a variety of reasons. Even some realists have (...) appealed to a PI. My goal is to advance our understanding of what the various PIs can teach us about science and the threat posed by PIs to scientific realism. (shrink)

In recent years, the argument from inductive risk against value free science has enjoyed a revival. This paper investigates and clarifies this argument through means of a case-study: neonicitinoid research. Sect. 1 argues that the argument from inductive risk is best conceptualised as a claim about scientists’ communicative obligations. Sect. 2 then shows why this argument is inapplicable to “public communication”. Sect. 3 outlines non-epistemic reasons why non-epistemic values should not play a role in public communicative contexts. Sect. 4 analyses (...) the implications of these arguments both for the specific case of neonicitinoid research and for understanding the limits of the argument from inductive risk. Sect. 5 sketches the broader implications of my claims for understanding the “Value Free Ideal” for science. (shrink)

Hailed by the Bulletin of the American Mathematical Society as "easy to use and a pleasure to read," this research monograph is recommended for students and professionals interested in model theory and definability theory. The sole prerequisite is a familiarity with the basics of logic, model theory, and set theory. 1974 edition.

Hilary Kornblith presents an account of inductive inference that addresses both its metaphysical and epistemological aspects. He argues that inductive knowledge is possible by virtue of the fit between our innate psychological capacities and the causal structure of the world. Kornblith begins by developing an account of natural kinds that has its origins in John Locke's work on real and nominal essences. In Kornblith's view, a natural kind is a stable cluster of properties that are bound together in nature. The (...) existence of such kinds serves as a natural ground of inductive inference. Kornblith then examines two features of human psychology that explain how knowledge of natural kinds is attained. First, our concepts are structured innately in a way that presupposes the existence of natural kinds. Second, our native inferential tendencies tend to provide us with accurate beliefs about the world when applied to environments that are populated by natural kinds. (shrink)

Itself a pleasure to read, this book is full of inventive arguments and conveys Millgram's bold thesis with elegance and force.

This introduction consists of two parts. In the first part, the special issue editors introduce inductive metaphysics from a historical as well as from a systematic point of view and discuss what distinguishes it from other modern approaches to metaphysics. In the second part, they give a brief summary of the individual articles in this special issue.

Sosa, Pritchard, and Vogel have all argued that there are cases in which one knows something inductively but does not believe it sensitively, and that sensitivity therefore cannot be necessary for knowledge. I defend sensitivity by showing that inductive knowledge is sensitive.

Pure Inductive Logic is the study of rational probability treated as a branch of mathematical logic. This monograph, the first devoted to this approach, brings together the key results from the past seventy years, plus the main contributions of the authors and their collaborators over the last decade, to present a comprehensive account of the discipline within a single unified context.

Drawing on past work, we introduce a new approach to the New Riddle of Induction, showing that the inductive projection of gruesome properties is unreliable under particular ideal conditions that are sufficient for the reliable inductive projection of non-gruesome properties. As an auxiliary to our account, we introduce rules for resolving conflicts between background information and the conclusions of otherwise reliable inductive inferences. Our approach to the New Riddle of Induction is quite permissive in the range of properties (...) it recognizes as suitable for inductive projection, allowing for the inductive projection of highly gerrymandered non-natural properties. However, as an addendum to our discussion of the New Riddle, we show that natural properties do form a more reliable basis for inductive projection in cases where one’s sample is small. (shrink)

Category-based induction is an inferential mechanism that uses knowledge of conceptual relations in order to estimate how likely is for a property to be projected from one category to another. During the last decades, psychologists have identified several features of this mechanism, and they have proposed different formal models of it. In this article; we propose a new mathematical model for category-based induction based on distances on conceptual spaces. We show how this model can predict most of the (...) properties of this kind of reasoning while providing a solid theoretical foundation for it. We also show that it subsumes some of the previous models proposed in the literature and that it generates new predictions. (shrink)

In this paper I adduce a new argument in support of the claim that IBE is an autonomous form of inference, based on a familiar, yet surprisingly, under-discussed, problem for Hume’s theory of induction. I then use some insights thereby gleaned to argue for the claim that induction is really IBE, and draw some normative conclusions.

I want to examine a possible solution to the problem of induction-one which, as far as I know, has not been discussed elsewhere. The solution makes crucial use of the notion of objective natural necessity. For the purposes of this discussion, I shall assume that this notion is coherent. I am aware that this assumption is controversial, but I do not have space to examine the issue here.

My first goal is to motivate a distinctively metaphysical approach to the problem of induction. I argue that there is a precise sense in which the only way that orthodox Humean and non-Humean views can justify induction is by appealing to extremely strong and unmotivated probabilistic biases. My second goal is to sketch what such a metaphysical approach could possibly look like. After sketching such an approach, I consider a toy case that illustrates the way in which such (...) a metaphysics can help us make progress on the problem of induction. (shrink)

In this article, I argue that arguments from the history of science against scientific realism, like the arguments advanced by P. Kyle Stanford and Peter Vickers, are fallacious. The so-called Old Induction, like Vickers's, and New Induction, like Stanford's, are both guilty of confirmation bias—specifically, of cherry-picking evidence that allegedly challenges scientific realism while ignoring evidence to the contrary. I also show that the historical episodes that Stanford adduces in support of his New Induction are indeterminate between (...) a pessimistic and an optimistic interpretation. For these reasons, these arguments are fallacious, and thus do not pose a serious challenge to scientific realism. (shrink)

Most social policies cannot be defended without making inductive inferences. For example, consider certain arguments for racial profiling and affirmative action, respectively. They begin with statistics about crime or socioeconomic indicators. Next, there is an inductive step in which the statistic is projected from the past to the future. Finally, there is a normative step in which a policy is proposed as a response in the service of some goal—for example, to reduce crime or to correct socioeconomic imbalances. In comparison (...) to the normative step, the inductive step of a policy defense may seem trivial. We argue that this is not so. Satisfying the demands of the inductive step is difficult, and doing so has important but underappreciated implications for the normative step. In this paper, we provide an account of induction in social contexts and explore its implications for policy. Our account helps to explain which normative principles we ought to accept, and as a result it can explain why it is acceptable to make inferences involving race in some contexts (e.g., in defense of affirmative action) but not in others (e.g., in defense of racial profiling). (shrink)

In my 2007 paper, “Is There a Problem of Induction for Mathematics?” I rejected the idea that enumerative induction has force for mathematical claims. My core argument was based on the fact that we are restricted to examining relatively small numbers, so our samples are always biased, and hence they carry no inductive weight. In recent years, I have come to believe that this argument is flawed. In particular, while arithmetical samples are indeed biased, my new view is (...) that this bias actually strengthens the inductive support that accrues from them. The reason is that small numbers typically provide a more severe test of general arithmetical claims due to the greater frequency of significant properties and boundary cases among such numbers. In this paper, I describe and defend this new view, which a call Positive Bias Pro-Inductivism. (shrink)

I review prominent historical arguments against scientific realism to indicate how they display a systematic overshooting in the conclusions drawn from the historical evidence. The root of the overshooting can be located in some critical, undue presuppositions regarding realism. I will highlight these presuppositions in connection with both Laudan’s ‘Old induction’ and Stanford’s New induction, and then delineate a minimal realist view that does without the problematic presuppositions.

Views which deny that there are necessary connections between distinct existences have often been criticized for leading to inductive skepticism. If there is no glue holding the world together then there seems to be no basis on which to infer from past to future. However, deniers of necessary connections have typically been unconcerned. After all, they say, everyone has a problem with induction. But, if we look at the connection between induction and explanation, we can develop the problem (...) of induction in a way that hits deniers of necessary connections, but not their opponents. The denier of necessary connections faces an `internal' problem with induction -- skepticism about important inductive inferences naturally flows from their position in a way that it doesn't for those who accept necessary connections. This is a major problem, perhaps a fatal one, for the denial of necessary connections. (shrink)

This paper formulates some paradoxes of inductive knowledge. Two responses in particular are explored: According to the first sort of theory, one is able to know in advance that certain observations will not be made unless a law exists. According to the other, this sort of knowledge is not available until after the observations have been made. Certain natural assumptions, such as the idea that the observations are just as informative as each other, the idea that they are independent, and (...) that they increase your knowledge monotonically (among others) are given precise formulations. Some surprising consequences of these assumptions are drawn, and their ramifications for the two theories examined. Finally, a simple model of inductive knowledge is offered, and independently derived from other principles concerning the interaction of knowledge and counterfactuals. (shrink)

"Here the author of How to Solve It explains how to become a "good guesser." Marked by G. Polya's simple, energetic prose and use of clever examples from a wide range of human activities, this two-volume work explores techniques of guessing, inductive reasoning, and reasoning by analogy, and the role they play in the most rigorous of deductive disciplines."--Book cover.

Originally published in 1973. This book presents a valid mode of reasoning that is different to mathematical probability. This inductive logic is investigated in terms of scientific investigation. The author presents his criteria of adequacy for analysing inductive support for hypotheses and discusses each of these criteria in depth. The chapters cover philosophical problems and paradoxes about experimental support, probability and justifiability, ending with a system of logical syntax of induction. Each section begins with a summary of its contents (...) and there is a glossary of technical terms to aid the reader. (shrink)

The standard backward-induction reasoning in a game like the centipede assumes that the players maintain a common belief in rationality throughout the game. But that is a dubious assumption. Suppose the first player X didn't terminate the game in the first round; what would the second player Y think then? Since the backwards-induction argument says X should terminate the game, and it is supposed to be a sound argument, Y might be entitled to doubt X's rationality. Alternatively, Y (...) might doubt that X believes Y is rational, or that X believes Y believes X is rational, or Y might have some higher-order doubt. X’s deviant first move might cause a breakdown in common belief in rationality, therefore. Once that goes, the entire argument fails. The argument also assumes that the players act rationally at each stage of the game, even if this stage could not be reached by rational play. But it is also dubious to assume that past irrationality never exerts a corrupting influence on present play. However, the backwards-induction argument can be reconstructed for the centipede game on a more secure basis.1 It may be implausible to assume a common belief in rationality throughout the game, however the game might go, but the argument requires less than this. The standard idealisations in game theory certainly allow us to assume a common belief in rationality at the beginning of the game. They also allow us to assume this common belief persists so long as no one makes an irrational move. That is enough for the argument to go through. (shrink)

Applying good inductive rules inside the scope of suppositions leads to implausible results. I argue it is a mistake to think that inductive rules of inference behave anything like 'inference rules' in natural deduction systems. And this implies that it isn't always true that good arguments can be run 'off-line' to gain a priori knowledge of conditional conclusions.

This article challenges the assumption that novel conceptual and theoretical work should be generated through induction from existing literature. While induction remains valuable in empirical inquiry, its role changes when the object of inquiry is not observed phenomena but inherited concepts, theories, and frameworks. In conceptual and metatheoretical work, premature induction from the literature can constrain originality by anchoring inquiry within the existing possibility-space of a field. The article develops a creativity-based critique of induction, distinct from (...) the classical philosophical critique associated with Hume. The problem is not that induction lacks logical justification, but that it may prematurely narrow the imagination. To support this claim, the article examines a representative set of influential theories in four fields — psychology, sociology, leadership studies, and cognitive science/philosophy of mind — finding that across all four, the large majority of major theories did not emerge through strict literature-first induction, but through abductive, interpretive, metaphorical, clinical, historical, normative, or architectonic moves later refined through evidence, literature, and application. Drawing on the phenomenological distinction between filling and emptying, the concept of beginner's mind, and the expert's internalized literature, the article argues that formal literature review at the generative stage is not merely unnecessary for expert theorists — it is phenomenologically counter-productive. An alternative seven-stage sequence is proposed, repositioning the literature review as a situating and novelty-confirming device that performs its best work after, not before, the generative act. Boundary conditions are discussed, with particular attention to the role of expertise: the critique applies most strongly to expert theorists and least to novice researchers for whom the literature review still serves a genuine capacity-building function. (shrink)

Aristotle said that induction (epagōgē) is a proceeding from particulars to a universal, and the definition has been conventional ever since. But there is an ambiguity here. Induction in the Scholastic and the (so-called) Humean tradition has presumed that Aristotle meant going from particular statements to universal statements. But the alternate view, namely that Aristotle meant going from particular things to universal ideas, prevailed all through antiquity and then again from the time of Francis Bacon until the mid-nineteenth (...) century. Recent scholarship is so steeped in the first-mentioned tradition that we have virtually forgotten the other. In this essay McCaskey seeks to recover that alternate tradition, a tradition whose leading theoreticians were William Whewell, Francis Bacon, Socrates, and in fact Aristotle himself. The examination is both historical and philosophical. The first part of the essay fills out the history. The latter part examines the most mature of the philosophies in the Socratic tradition, specifically Bacon’s and Whewell’s. After tracing out this tradition, McCaskey shows how this alternate view of induction is indeed employed in science, as exemplified by several instances taken from actual scientific practice. In this manner, McCaskey proposes to us that the Humean problem of induction is merely an artifact of a bad conception of induction and that a return to the Socratic conception might be warranted. (shrink)

Writing on the justification of certain inductive inferences, the author proposes that sometimes induction is justified and that arguments to prove otherwise are not cogent. In the first part he defends the argument of D.C. Williams' The Ground of Induction that induction is justified as a matter of logic by the proportional syllogism: "The vast majority of large samples match the population, therefore (probably) this sample matches the population"). In the second part he deals with such topics (...) as deductive logic (arguing that deductive logic is not formal), the theory of logical probability, and probability and truth. (shrink)

In ‘Induction and Natural Kinds’, I proposed a solution to the problem of induction according to which our use of inductive inference is reliable because it is grounded in the natural kind structure of the world. When we infer that unobserved members of a kind will have the same properties as observed members of the kind, we are right because all members of the kind possess the same essential properties. The claim that the existence of natural kinds is (...) what grounds reliable use of induction is based on an inference to the best explanation of the success of our inductive practices. As such, the argument for the existence of natural kinds employs a form of ampliative inference. But induction is likewise a form of ampliative inference. Given both of these facts, my account of the reliability of induction is subject to the objection that it provides a circular justification of induction, since it employs an ampliative inference to justify an ampliative inference. In this paper, I respond to the objection of circularity by arguing that what justifies induction is not the inference to the best explanation of its reliability. The ground of induction is the natural kinds themselves. (shrink)

The current state of inductive logic is puzzling. Survey presentations are recurrently offered and a very rich and extensive handbook was entirely dedicated to the topic just a few years ago [23]. Among the contributions to this very volume, however, one finds forceful arguments to the effect that inductive logic is not needed and that the belief in its existence is itself a misguided illusion, while other distinguished observers have eventually come to see at least the label as “slightly antiquated”.What (...) seems not to have lost any of its currency is the problem which inductive logic is meant to address. Inference from limited ascertained information to uncertain hypotheses is ubiquitous in learning, prediction and discovery. The logical insight that such kind of inference is fallible m.. (shrink)

Traditional attempts to understanding inductive reasoning in science have typically involved analyzing language, focusing on statements or propositions. However, recent arguments suggest that this approach misconceives induction, prompting the need for a new perspective. This study offers a fresh view on induction by integrating William Whewell's theory of induction, which distinguishes two forms of reasoning: interpretation and representation. This perspective suggests that induction can be seen as a reasoning process based on semantic and pragmatic models rather (...) than statements or propositions. (shrink)

This paper defends a new argument in the spirit of Golemon and Graber’s Deductive No-Miracles Argument (DNMA) for scientific realism, recently criticized by Kok Yong Lee. While Lee argues that the DNMA is invalid or leads to a collapse in probability assignments, I develop an Inductive No-Miracles Argument (INMA) that preserves logical strength without relying on abductive inference or explanatory premises. By introducing an “approximately equal” probabilistic operator (≈), I show how probabilistic reasoning can license a strong inductive inference without (...) collapsing probability calculus. The resulting INMA satisfies the desiderata motivating the DNMA and clarifies how probabilistic reasoning can underwrite realist inference without appeal to explanatory virtue. Moreover, the structure argued for seems ripe for use in other contexts where avoiding abduction in lieu of less theory-laden probability is attractive, such as fine-tuning arguments and evolutionary debunking arguments. (shrink)

I attempt to refute Hume’s problem of induction. I raise the problem of counter-induction. I develop a template for generating philosophical problems. I develop and defend stage theory of scientific development for scientific realism. I develop and defend two new metaethical theories: cultural emotivism and moral functionalism. I argue that to compare morality to mathematics is to lose credibility. I develop the problem of moral induction against moral realism.

My aim is to evaluate a new realist strategy for addressing the pessimistic induction, Ludwig Fahrbach’s (Synthese 180:139–155, 2011) appeal to the exponential growth of science. Fahrbach aims to show that, given the exponential growth of science, the history of science supports realism. I argue that Fahrbach is mistaken. I aim to show that earlier generations of scientists could construct a similar argument, but one that aims to show that the theories that they accepted are likely true. The problem (...) with this is that from our perspective on the history of science we know their argument is flawed. Consequently, we should not be impressed or persuaded by Fahrbach’s argument. Fahrbach has failed to identify a difference that matters between today’s theories and past theories. But realists need to find such a difference if they are to undermine the pessimistic induction. (shrink)

This paper scrutinises the limits of a posteriori induction in acquiring modal knowledge. I focus on my similarity-based account (Roca-Royes [2017]); an inductive, non-rationalist epistemology of modality about concrete entities. Despite the explanatory merits of the account in relation to a vast range of modal claims, this inductive epistemology has been found incapable of yielding knowledge of a certain, other range of modal claims. Here, two notions of knowability are distinguished which reveal some of these limitations to be not (...) only accidental to the method but also virtuous. Additionally, the scrutiny suggests a recipe for increasingly pushing back, as modal enquirers, some of these limits. Limits will irremediably remain. But, as modal epistemologists, it is to explain what lies beyond these irremediable limits (not within) that we should look somewhere else. (shrink)

There is enormous excitement surrounding AI technology. This excitement is driven, at least in part, by hype: exaggerated claims about the capabilities of AI. Since AI is an inherently interesting and sensational topic, and since there has been a lot of hype claims made about it, discussions of AI in public discourse are suffused with hype. These hype conditions have significant potential consequences concerning distribution of resources and environmental damage. This paper argues that these hype conditions also pose a distinct (...) risk for researchers who work on AI. In short, the risk is that, in hype conditions, ordinary research activities and communication may unintentionally contribute to hype. Research is often exploratory or involves arguing for hypotheses that are not accepted as scientific consensus. Furthermore, there is always a chance that even excellent science will result in error; this is known as inductive risk. However, not all errors have the same consequences. Sometimes, accepting a false hypothesis can have worse consequences than rejecting a true one, or vice versa. A researcher might, quite reasonably, argue in a published article for a hypothesis about AI that turns out to be false. At the same time, because of the hype conditions surrounding AI, the article may be read by a much wider audience than they intend. Thus, when arguing for hypotheses, researchers run an inductive risk of contributing to AI hype. This risk needs to be considered by researchers when deciding how to conduct inquiry and communicate their results. (shrink)

The argument from inductive risk is considered to be one of the strongest challenges for value-free science. A great part of its appeal lies in the idea that even an ideal epistemic agent—the “perfect scientist” or “scientist qua scientist”—cannot escape inductive risk. In this paper, I scrutinize this ambition by stipulating an idealized Bayesian decision setting. I argue that inductive risk does not show that the “perfect scientist” must, descriptively speaking, make non-epistemic value-judgements, at least not in a way that (...) undermines the value-free ideal. However, the argument is more successful in showing that there are cases where the “perfect scientist” should, normatively speaking, use non-epistemic values. I also show that this is possible without creating problems of illegitimate prescription and wishful thinking. Thus, while inductive risk does not refute value-freedom completely, it still represents a powerful critique of value-free science. (shrink)

In this paper, we analyse conceptions of induction and certainty in Wolff and Crusius, highlighting their competing conceptions of physics. We discuss (i) the perspective of Wolff, who assigned induction an important role in physics, but argued that physics should be an axiomatic science containing certain statements, and (ii) the perspective of Crusius, who adopted parts of the ideal of axiomatic physics but criticized the scope of Wolff’s ideal of certain science. Against interpretations that take Wolff’s proofs in (...) physics to be based on empirical statements that are probable, we show how inductively established statements, coupled with assumptions concerning the uniformity of nature, can be certain according to Wolff. We examine Crusius’ little known work on physics and show that he attacked Wolff, arguing that many statements of physics are probable. We provide a discussion of the reception of methodological rules similar to Newton’s Regulae Philosophandi, discussing different interpretations of such rules. We conclude by briefly hinting at how the debate between Wolff and Crusius provides historical context for understanding Kant’s philosophy of natural science. (shrink)

There are nine antirealist explanations of the success of science in the literature. I raise difficulties against all of them except the latest one, and then construct a pessimistic induction that the latest one will turn out to be problematic because its eight forerunners turned out to be problematic. This pessimistic induction is on a par with the traditional pessimistic induction that successful present scientific theories will be revealed to be false because successful past scientific theories were (...) revealed to be false. (shrink)

This chapter discusses the philosophical viability of Ottmar Edenhofer and Martin Kowarsch’s proposed pragmatic-enlightened model of science advising, as well as the practical application of their proposed model to the case of climate science advising. Edenhofer and Kowarsch’s model makes central use of a cartographic metaphor—one in which scientists and policymakers craft and consider different scientific routes to various value-laden ethical, political, and social destinations. But the argument from inductive risk poses a significant challenge to the viability of the metaphor, (...) and hence, to the workability of the model. The chapter opens with a discussion of the challenge that inductive risk poses for the pragmatic-enlightened model, and closes with a discussion of how stakeholder engagement must be reconceived in order to meet that challenge. (shrink)